Mining Transportation Information From Social Media for Planned and Unplanned Events

Zhang, Zhenhua; Ni, Ming; Gao, Jing; He, Qing; University at Buffalo, SUNY

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Mining Transportation Information From Social Media for Planned and Unplanned Events

2016-05-01
By Zhang, Zhenhua ; Ni, Ming ; Gao, Jing ; ...

[PDF-1.15 MB]

English

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Details:

Creators:

Zhang, Zhenhua ; Ni, Ming ; Gao, Jing ; He, Qing

Zhang, Zhenhua ; Ni, Ming ; Gao, Jing ; He, Qing Less -
Corporate Creators:

University at Buffalo, SUNY
Corporate Contributors:

University Transportation Centers Program (U.S.) ; United States. Department of Transportation

University Transportation Centers Program (U.S.) ; United States. Department of Transportation Less -
Subject/TRT Terms:

[+]

Association Rules Data Mining Event Identification Information Retrieval Research Hub Ridership Social Media Social Sensing Subway Passenger Flow Prediction Subways Traffic Accident Detection Traffic Flow Traffic Signature Traffic Surge Transit Ridership Tweet Analysis Twitter Concentration
Resource Type:

Tech Report
Geographical Coverage:

New York ; United States

New York ; United States Less -
Corporate Publisher:

University Transportation Centers Program (U.S.)
Abstract:

The objective of this project is on mining social media data to deduce useful traveler’s information with a special emphasis under events, including both planned events (such as sporting games), and unplanned events (such as traffic accidents). Specifically, the project proposes to develop effective and efficient techniques to collect, extract and mine social media data to support advanced traveler information systems and traffic operators. By mining social media based semantics, especially text semantics, this project aims to achieve the following aims: 1) Forecast transit ridership under large sporting games; 2) Identify causality between abnormal traffic flow pattern and social media data; 2) Detect traffic accident using online social media data and traffic loop-detector data.
Format:

PDF
Funding:

DTRT13-G-UTC48
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:5e6121be99ae4fa67625bcfeb7a540d9cf930981e131615227d1085fb95fe4e3
Download URL:

https://rosap.ntl.bts.gov/view/dot/30838/dot_30838_DS1.pdf
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Mining Transportation Information From Social Media for Planned and Unplanned Events

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